Blip Vqa Finetuned
This model is a fine-tuned version of Salesforce/blip-vqa-base on an unknown dataset. It achieves the following results on the evaluation set: Loss: 2.1477
Fuente del modelo
- Tipo
- Text model
- Tamaño del archivo
- 1,43 GB
- Modelo base
- Salesforce/blip-vqa-base
- Versión
- vFP32
- Actualizado
- 30 oct 2026
- Descargas
- 21
- Fuente
- Hugging Face
Descripción de la fuente
blip-vqa-finetuned
This model is a fine-tuned version of Salesforce/blip-vqa-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.1477
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.7798 | 1.0 | 2000 | 2.4921 |
| 2.0263 | 2.0 | 4000 | 2.2244 |
| 1.6854 | 3.0 | 6000 | 2.1477 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
Fuentes
1 fuente
Fuentes
1 fuenteVerificado 30 oct
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Repository files
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Artefactos del modelo
1 artefacto
Artefactos del modelo
1 artefactomodel.safetensors
safetensors · FP32 (tensor header) · 1,43 GB · SHA-256 6c99da70f4f3…3535 · Hugging Face
Download fileExtractos de fuentes
3 extractos
Extractos de fuentes
3 extractos--- library_name: transformers license: bsd-3-clause base_model: Salesforce/blip-vqa-base tags: - generated_from_trainer model-index: - name: blip-vqa-finetuned results: [] --- <!-- This model card has been generated automatically according to the information the Trainer had access to. You should probably proofread and complete it, then remove this comment. --> # blip-vqa-finetuned This model is a fine-tuned version of [Salesforce/blip-vqa-base](https://huggingface.co/Salesforce/blip-vqa-base) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.1477 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 4 - eval_batch_size: 4 - seed: 42 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 3 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 2.7798 | 1.0 | 2000 | 2.4921 | | 2.0263 | 2.0 | 4000 | 2.2244 | | 1.6854 | 3.0 | 6000 | 2.1477 | ### Framework versions - Transformers 4.47.0 - Pytorch 2.5.1+cu121 - Datasets 3.2.0 - Tokenizers 0.21.0
Source context: 21 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo VietKien/blip-vqa-finetuned
Source context: 7 downloads · 0 likes · Pipeline visual-question-answering · Library transformers · Repo VietKien/blip-vqa-finetuned
